collaborators

5 papers

cs.CL2026

SAGE: A Search-AuGmented Evaluation of Large Language Models on Free-Form QA

Sher Badshah, Ali Emami, Hassan Sajjad

As Large Language Models (LLMs) become increasingly used for question-answering (QA), relying on static, pre-annotated references for evaluation poses significant challenges in cos…

cs.CL2026

SCOPE: Selective Conformal Optimized Pairwise LLM Judging

Sher Badshah, Ali Emami, Hassan Sajjad

Large language models (LLMs) are increasingly used as scalable judges in pairwise evaluation, but they remain prone to miscalibration and biases. We propose \textsc{Scope} (Selecti…

cs.CL2025

CLEV: LLM-Based Evaluation Through Lightweight Efficient Voting for Free-Form Question-Answering

Sher Badshah, Moamen Moustafa, Hassan Sajjad

Evaluating free-form Question Answering (QA) remains a challenge due to its diverse and open-ended nature. Traditional automatic metrics fail to capture semantic equivalence or acc…

cs.CL2025

Reference-Guided Verdict: LLMs-as-Judges in Automatic Evaluation of Free-Form QA

Sher Badshah, Hassan Sajjad

The emergence of Large Language Models (LLMs) as chat assistants capable of generating human-like conversations has amplified the need for robust evaluation methods, particularly f…

cs.MA2025

Static Sandboxes Are Inadequate: Modeling Societal Complexity Requires Open-Ended Co-Evolution in LLM-Based Multi-Agent Simulations

Jinkun Chen, Sher Badshah, Xuemin Yu +1

What if artificial agents could not just communicate, but also evolve, adapt, and reshape their worlds in ways we cannot fully predict? With llm now powering multi-agent systems an…